The implementation of categorical accuracy. More...
#include <metric.h>
Inheritance diagram for CategoricalAccuracy:
Public Member Functions | |
| CategoricalAccuracy () | |
| Constructor of CategoricalAccuracy. | |
| float | calculateMetric (const sTensor &targets, const sTensor &predictions) override |
| Calcualate the current value of the metric given the new batches of targets and predictions. More... | |
| std::string | getShortName () const override |
| Short string identifier of the metric. More... | |
 Public Member Functions inherited from Metric | |
| Metric () | |
| Constructor for the Metric class. More... | |
| void | reset () |
Reset the metric, i.e.: set numSamples and currentTotalMetric to 0. | |
Additional Inherited Members | |
| Protected Attributes inherited from Metric | |
| size_t | numSamples |
| The number of samples processed so far. | |
| float | currentTotalMetric |
| The current total value of the metric. | |
Detailed Description
The implementation of categorical accuracy.
This metric requires the targets to consist of only 0s and 1s, with 1s corresponding to the correct class. The rows are the samples, the columns are the classes. The predictions can consist of any real value, the largest value is assumed to be the predicted class.
- Examples
- MNIST.
Member Function Documentation
◆ calculateMetric()
|
overridevirtual |
Calcualate the current value of the metric given the new batches of targets and predictions.
- Parameters
-
targets The desired outputs of the network. predictions The actual outputs of the network.
- Returns
- The value of the metric.
Implements Metric.
◆ getShortName()
|
overridevirtual |
Short string identifier of the metric.
Used when printing the value of the metric to the terminal.
- Returns
- A string identifier of the metric.
Implements Metric.
The documentation for this class was generated from the following files:
- include/metric.h
- src/ann/metrics/categorical_accuracy.cpp
